A database deployment infrastructure can be a service layer of a database management system that simplifies the deployment of database objects and other design time artifacts by providing a declarative approach for defining these design time artifacts and ensuring a consistent deployment into the database management system environment (DBMS), based on a transactional all-or-nothing deployment model and implicit dependency management. Such an approach can leverage capabilities of a modern high-speed DBMS, such as for example the HANA in-memory DBMS (IM-DBMS) available from SAP SE of Walldorf, Germany, which can provide very high performance relative to disk-based approaches.
Using various customization-enabling integrated development environments (IDE), such as for example the HANA Studio available for use with the HANA IM-DBMS (available from SAP SE of Walldorf, Germany), a user may, using a group of design time artifacts, create information models, tables, landscapes, and the like, a different system than that on which a DBMS is executed.
Some database systems use in-memory on-line analytical processing (OLAP), such as for processing databases sized at several terabytes (or more), tables with billions (or more) of rows, and the like. In some database system, on-disk OLAP (e.g., “big data,” analytics servers for advanced analytics, data warehousing, business intelligence environments, and the like) is used, such as for databases sized at several petabytes or even more, tables with up to trillions of rows, and the like. Instruction sets can be configured for processing by an OLAP engine and, for example, can join and/or provide views of one or more tables. Some instructions or features associated with such instruction sets are not compatible with engines other than OLAP engines. Therefore, processing of such instruction sets in a system that does not include an OLAP engine can result in processing errors and reduced processing speeds.